By combining the strengths of human and computers, Human Machine Collaborative Decision Making has been shown to generate higher quality solutions in less time than conventional computerized methods. In many cases, it is difficult to model continually changing problems and incorporate human objectives into the solution. Human-guided algorithms (HGAs) harness the power of sophisticated algorithms and computers to provide flexibility to the human decision maker to model correctly and dynamically the problem and steer the algorithm to solutions that match his/her objectives for the given problem. HGAs are designed to make the power of Operations Research accessible to problem domain experts and decision makers, and incorporate their expert knowledge into every solution. In order to appropriately utilize algorithms during a planner's decision making, HGA operators must appropriately trust the HGA and the final solution. Through the use of trust-based design (TBD), it was hypothesized that users of the HGA will gain better insight into the solution process, improve their calibration of trust, and generate superior solutions. The application of TBD requires the consideration of algorithms, solution steering methods, and displays required to best match human and computer complimentary strengths and to generate solutions that can be appropriately trusted.(cont.) Abstract hierarchy, Ecological Interface Design, and various trust models are used to ensure that the HGA operators' evaluation of trust can be correctly calibrated to all necessary HGA trust attributes. A human-subject evaluation was used to test the effectiveness of the TBD design approach for HGAs. An HGA, including the appropriate controls and displays, was designed and developed using the described TBD approach. The participants were presented with the task of using the HGA to develop a routing plan for military aircraft to prosecute enemy targets. The results showed that TBD had a significant effect on trust, HGA performance, and in some cases the quality of final solutions. Another finding was that, HGA operators must be provided with additional trust related information to improve their understanding of the HGA, the solution process, and the final solution in order to calibrate properly their trust in the system.